Magistro darbe pristatoma sukurta programa, realizuojanti interneto naršyklės valdymą balsu. Ši programa papildo atskirų žodžių prototipinę atpažinimo sistemą, pagrįstą paslėptaisiais Markovo modeliais (PMM). Šios dvi dalys ir sudaro interneto naršyklės valdymo balsu prototipą, kuris gali atpažinti 71 komandą (vienas arba du žodžiai) lietuvių kalba: 1 komandą, skirtą naršyklės atvėrimui, 54 naršyklės valdymo komandas, 16 komandų, atveriančių konkrečius iš anksto sistemai nurodytus tinklalapius. Darbe aprašytas lietuvių kalbos atskirų žodžių atpažinimo sistemos akustinių modelių, grįstų paslėptaisiais Markovo modeliais, rinkinių eksperimentinis tyrimas. Atsižvelgiant į įvairius atpažinimui turinčius įtakos veiksnius (mokymo duomenų kiekį, mišinio komponenčių skaičių, kalbėtojo lytį, skirtingos techninės įrangos naudojimą atpažinime), buvo sukurti skirtingi balso komandų akustinių modelių rinkiniai. Eksperimentinio tyrimo metu buvo tiriama šių rinkinių panaudojimo atpažinimo sistemoje įtaka sistemos atpažinimo tikslumui. Eksperimentinio tyrimo rezultatai parodė, kad interneto naršyklės valdymo balsu sistemos prototipo atpažinimo tikslumas siekia 98%. Sistema gali būti naudojama kaip vaizdinė priemonė vyresniųjų klasių moksleiviams informacinių technologijų, fizikos, psichologijos, matematikos pamokose. / The thesis presents a prototype of the software (system) for Web browser control by voice. The prototype consists of two parts: the Hidden Markov Models based word recognition system and the program, which implements browser control by voice commands and is integrated in the word recognition system. The prototype is a speaker-independent Lithuanian word (voice commands) recognition system and can recognize 71 voice commands: 1 command is intended to run browser, 54 commands – for browser control, and 16 commands – to open various user predefined websites. Taking into account various factors (amount of training data, number of Gaussian mixture components, gender of speaker, use of different hardware for recognition) which have impact on recognition, different sets of acoustic models of Lithuanian voice commands were created and trained. An experimental investigation of the influence of the sets usage in Lithuanian word recognition system on the word recognition accuracy was performed. The results of the experimental investigation showed that created prototype system achieves 98% word recognition accuracy. The prototype system can be used at secondary school as a visual speech recognition learning tool in the informatics, physics, psychology, and mathematics lessons for the pupils of senior classes.

Disertacija skirta logistinei ekonominių ciklų analizei. Darbo tikslas - vadovaujantis ekonomine logistine teorija atskleisti ir nustatyti ciklinio ekonominio svyravimo priežastis. Darbe atliekama teorinė, logistinė ir empirinė ciklinių ekonominių svyravimų analizė. Įvertinant ekonominės logistinės teorijos nuostatas, patikslinama ekonominio ciklo samprata, parengiamas teorinis logistinis ekonominio ciklo modelis ir logistinis ciklinio ekonominės sistemos svyravimo ir raidos tyrimo modelis. Darbe atskleidžiamos vidutinės trukmės ekonominių ciklų susiformavimą veikiančios giluminės priežastys. Nustatoma inovacinių procesų įtaka rinkos susiformavimui, rinkos talpos uždarumo įtaka rinkos kaitimui, rinkos prisotinimui ir paslėptosios perprodukcijos bei burbulo proceso susiformavimui. Taip pat atskleidžiama visų minėtų procesų ir ekonominių paradoksų (didėjančio pelningumo paradokso ir skolos spąstų paradokso) įtaka ekonominio ciklo formavimuisi ir veikimui. / Dissertation deals with logistical analysis of economic cycles. Aim of the research - to reveal and to determine causes of cyclical economic fluctuations, according to economic logistic theory. Theoretical, logistical and empirical analyses of cyclical economic fluctuations are carried out in the work. Conception of economic cycle is specified. Evaluating provisions of economic logistic theory, two models are created – theoretical logistic economic cycle model and logistic economic system‘s cyclical fluctuation and development research model. In the dissertation the deep causes of economic cycles influencing their formation are revealed. The influence of innovative processes to the market formation, the impact of market capacity limitation to the market heating, saturation, hidden overproduction and to the formation of bubble process are determined. The influence of all the mentioned processes as well as economic paradoxes ((growing profitability paradox and credit trap paradox)) to the formation and working of economic cycle are revealed.

Dissertation deals with logistical analysis of economic cycles. Aim of the research - to reveal and to determine causes of cyclical economic fluctuations, according to economic logistic theory. Theoretical, logistical and empirical analyses of cyclical economic fluctuations are carried out in the work. Conception of economic cycle is specified. Evaluating provisions of economic logistic theory, two models are created – theoretical logistic economic cycle model and logistic economic system‘s cyclical fluctuation and development research model. In the dissertation the deep causes of economic cycles influencing their formation are revealed. The influence of innovative processes to the market formation, the impact of market capacity limitation to the market heating, saturation, hidden overproduction and to the formation of bubble process are determined. The influence of all the mentioned processes as well as economic paradoxes ((growing profitability paradox and credit trap paradox)) to the formation and working of economic cycle are revealed. / Disertacija skirta logistinei ekonominių ciklų analizei. Darbo tikslas - vadovaujantis ekonomine logistine teorija atskleisti ir nustatyti ciklinio ekonominio svyravimo priežastis. Darbe atliekama teorinė, logistinė ir empirinė ciklinių ekonominių svyravimų analizė. Įvertinant ekonominės logistinės teorijos nuostatas, patikslinama ekonominio ciklo samprata, parengiamas teorinis logistinis ekonominio ciklo modelis ir logistinis ciklinio ekonominės sistemos svyravimo ir raidos tyrimo modelis. Darbe atskleidžiamos vidutinės trukmės ekonominių ciklų susiformavimą veikiančios giluminės priežastys. Nustatoma inovacinių procesų įtaka rinkos susiformavimui, rinkos talpos uždarumo įtaka rinkos kaitimui, rinkos prisotinimui ir paslėptosios perprodukcijos bei burbulo proceso susiformavimui. Taip pat atskleidžiama visų minėtų procesų ir ekonominių paradoksų (didėjančio pelningumo paradokso ir skolos spąstų paradokso) įtaka ekonominio ciklo formavimuisi ir veikimui.

Modern speech communication technologies expose users to perceptual quality degradations that were not experienced earlier with conventional telephone systems. Since perceived speech quality is a major contributor to the end user's perception of quality of service, speech quality estimation has become an important research field. In this dissertation, perceptual quality estimators are proposed for several emerging speech communication applications, in particular for i) wireless communications with noise suppression capabilities, ii) wireless-VoIP communications, iii) far-field hands-free speech communications, and iv) text-to-speech systems. First, a general-purpose speech quality estimator is proposed based on statistical models of normative speech behaviour and on innovative techniques to detect multiple signal distortions. The estimators do not depend on a clean reference signal hence are termed ``blind." Quality meters are then distributed along the network chain to allow for both quality degradations and quality enhancements to be handled. In order to improve estimation performance for wireless communications, statistical models of noise-suppressed speech are also incorporated. Next, a hybrid signal-and-link-parametric quality estimation paradigm is proposed for emerging wireless-VoIP communications. The algorithm uses VoIP connection parameters to estimate a base quality representative of the packet switching network. Signal-based distortions are then detected and quantified in order to adjust the base quality accordingly. The proposed hybrid methodology is shown to overcome the limitations of existing pure signal-based and pure link parametric algorithms. Temporal dynamics information is then investigated for quality diagnosis for hands-free speech communications. A spectro-temporal signal representation, where speech and reverberation tail components are shown to be separable, is used for blind characterization of room acoustics. In particular, estimators of reverberation time, direct-to-reverberation energy ratio, and reverberant speech quality are developed. Lastly, perceptual quality estimation for text-to-speech systems is addressed. Text- and speaker-independent hidden Markov models, trained on naturally produced speech, are used to capture normative spectral-temporal information. Deviations from the models, computed by means of a log-likelihood measure, are shown to be reliable indicators of multiple quality attributes including naturalness, fluency, and intelligibility. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-12-22 14:54:49.28

This thesis consists of three essays. The first essay, “A Theory of Bank Illiquidity and Default with Hidden Trades”, develops a theory of banking to explore how the availability of trading opportunities for both banks and individual investors affects the link between illiquidity and default in the financial system. The results show that default emerges only in the presence of systemic risk, and when an unpredicted crisis hits the economy. Moreover, in contrast to the previous literature, default is not an efficient outcome of the economy. The second essay, “Financial Liberalization with Hidden Trades”, studies how the availability of unregulated market-based channels for the circulation of liquidity in the financial system affects the process of financial integration, and the efficiency of the corresponding equilibrium, in a two-country economy with comparative advantages. The results show that the only level of integration which the two countries are able to coordinate is the one where the two banking systems are autarkic, but international hidden trades are possible. Moreover, the resulting consumption allocation is constrained efficient. The third essay, “Bank Liquidity, Stock Market Participation, and Economic Growth”, develops a dynamic growth model with fully microfounded banks and markets to explain the observed decreasing trend in the relative liquidity of many financial systems around the world. The main result characterizes the threshold after which the agents in the economy are rich enough to access the market, where the relative liquidity is lower, and shows that the relative liquidity of the whole financial system (banks and markets) drops because of the increasing market participation. Some evidence consistent with this theoretical prediction is provided: a one-unit increase in an index of securities market liberalization leads to a drop in the relative liquidity of between 13 and 22 per cent.

microRNAs (miRNAs) are small (20-23 nt), non-coding single stranded RNA molecules that play an important role in post-transcriptional regulation of protein-coding genes. miRNAs have been found in all animal lineages, and have been implicated as critical regulators during development in multiple species. The echinoderms, Strongylocentrotus purpuratus (sea urchin) and Patiria miniata (sea star) are excellent model organisms for studying development due to their well-characterized transcriptional gene networks, ease of working with their embryos in the laboratory and phylogenetic position as invertebrate deuterostomes. Literature on miRNAs in echinoderm embryogenesis is limited. It has been shown that RNAi genes are developmentally expressed and regulated in sea urchin embryos, but no study in the sea urchin has examined the expression of miRNAs. The goal of my work has been to study miRNA regulation in echinoderm developmental gene networks. I have identified developmentally regulated miRNAs in sea urchin and sea star embryos, using a combination of computational and wet lab experimental techniques. I developed a probabilistic model (named HHMMiR) based on hierarchical hidden Markov models (HHMMs) to classify genomic hairpins into miRNA precursors and random stem-loop structures. I then extended this model to make an efficient decoder by introduction of explicit state duration densities. We used the Illumina Genome Analyzer to sequence small RNA libraries in mixed stage population of embryos from one to three days after fertilization of S. purpuratus and P. miniata. We developed a computational pipeline for analysis of these miRNAseq data to reveal the miRNA populations in both species, and study their differential expression. We also used northern blots and whole mount in situ hybridization experimental techniques to study the temporal and spatial expression patterns of some of these miRNAs in sea urchin embryos. By knocking down the major components of the miRNA biogenesis pathway, we studied the global effects of miRNAs on embryo morphology and differentiation genes. The biogenesis genes selected for this purpose are the RNAse III enzyme, Dicer and Argonaute. Dicer is necessary for the processing of mature miRNAs from hairpin structures while Ago is a necessary part of the RISC (RNA interference silencing complex) assembly, which is required for the miRNA to hybridize to its target mRNA site. Knocking down these genes hinders normal development of the sea urchin embryo and leads to loss of the larval skeleton, a novel phenotype not seen in sea stars, as well as abnormal gastrulation. Comparison of differentiation gene marker expression between control and Ago knocked down sea urchin embryos shows interesting patterns of expansion and suppression of adjoining some embryonic territories, while ingression of larval skeletogenesis progenitors does not occur.

This thesis is devoted to the problems of defining and developing the basic building blocks of an automated surveillance system. As its initial step, a background-modeling algorithm is described for segmenting moving objects from the background, which is capable of adapting to dynamic scene conditions, as well as determining shadows of the moving objects. After obtaining binary silhouettes for targets, object association between consecutive frames is achieved by a hypothesis-based tracking method. Both of these tasks provide basic information for higher-level processing, such as activity analysis and object identification. In order to recognize the nature of an event occurring in a scene, hidden Markov models (HMM) are utilized. For this aim, object trajectories, which are obtained through a successful track, are written as a sequence of flow vectors that capture the details of instantaneous velocity and location information. HMMs are trained with sequences obtained from usual motion patterns and abnormality is detected by measuring the distance to these models. Finally, MPEG-7 visual descriptors are utilized in a regional manner for object identification. Color structure and homogeneous texture parameters of the independently moving objects are extracted and classifiers, such as Support Vector Machine (SVM) and Bayesian plug-in (Mahalanobis distance), are utilized to test the performance of the proposed person identification mechanism. The simulation results with all the above building blocks give promising results, indicating the possibility of constructing a fully automated surveillance system for the future.

In this study, a new discriminative learning framework, called soft margin estimation (SME), is proposed for estimating the parameters of continuous density hidden Markov models (HMMs). The proposed method makes direct use of the successful ideas of margin in support vector machines to improve generalization capability and decision feedback learning in discriminative training to enhance model separation in classifier design. SME directly maximizes the separation of competing models to enhance the testing samples to approach a correct decision if the deviation from training samples is within a safe margin. Frame and utterance selections are integrated into a unified framework to select the training utterances and frames critical for discriminating competing models. SME offers a flexible and rigorous framework to facilitate the incorporation of new margin-based optimization criteria into HMMs training. The choice of various loss functions is illustrated and different kinds of separation measures are defined under a unified SME framework. SME is also shown to be able to jointly optimize feature extraction and HMMs. Both the generalized probabilistic descent algorithm and the Extended Baum-Welch algorithm are applied to solve SME. SME has demonstrated its great advantage over other discriminative training methods in several speech recognition tasks. Tested on the TIDIGITS digit recognition task, the proposed SME approach achieves a string accuracy of 99.61%, the best result ever reported in literature. On the 5k-word Wall Street Journal task, SME reduced the word error rate (WER) from 5.06% of MLE models to 3.81%, with relative 25% WER reduction. This is the first attempt to show the effectiveness of margin-based acoustic modeling for large vocabulary continuous speech recognition in a HMMs framework. The generalization of SME was also well demonstrated on the Aurora 2 robust speech recognition task, with around 30% relative WER reduction from the clean-trained baseline.

A piece of popular music is usually defined as a combination of vocal melody and instrumental accompaniment. People often start with the melody part when they are trying to compose or reproduce a piece of popular music. However, creating appropriate instrumental accompaniment part for a melody line can be a difficult task for non-musicians. Automation of accompaniment generation for vocal melodies thus can be very useful for those who are interested in singing for fun. Therefore, a computer software system which is capable of generating harmonic accompaniment for a given vocal melody input has been presented in this thesis. This automatic accompaniment system uses a Hidden Markov Model to assign chord to a given part of melody based on the knowledge learnt from a bank of vocal tracks of popular music. Comparing with other similar systems, our system features a high resolution key estimation algorithm which is helpful to adjust the generated accompaniment to the input vocal. Moreover, we designed a structure analysis subsystem to extract the repetition and structure boundaries from the melody. These boundaries are passed to the chord assignment and style player subsystems in order to generate more dynamic and organized accompaniment. Finally, prototype applications are discussed and the entire system is evaluated.

<p>The aim of this thesis was to explore and analyze the sponsored debates on Newsmill, so called seminars. How does the sponsor use Newsmills seminars for marketing purposes? Who is allowed to write in Newsmills seminars?</p><p>To answer these questions we used both a quantitative survey and a qualitative survey.</p><p>To examine how the sponsors use Newsmills seminars for marketing purposes we conducted a qualitative analysis which included three of the eleven seminars - a total of 26 articles. We examined how the sponsors conveyed the picture of themselves and if the written content in Newsmills seminars contained any hidden marketing. We could see that the sponsor has a great deal of influence on the seminars and also used them to market their brand with hybrid messages. Sponsors often tried to relate their brand to a public issue in order to camouflage their commercial purposes.</p><p>The quantitative survey aimed to map the seminars and answer the question “Who is allowed to write in Newsmills seminars?”. We observed how many of the writers were male/female, had a Swedish/foreign name, had a certain position in society and if the writer had any connection to, or wrote about, the sponsor. We examined all articles ever published in Newsmills seminars, up to the day of the survey. A total of 164 articles in 11 different seminars.</p><p>Our result showed that female writers are a minority group in Newsmills seminars. So are people with foreign names and people who lack a position which grants them authority.</p>